statsmodels.sandbox.stats.multicomp.ccols¶
- statsmodels.sandbox.stats.multicomp.ccols = array([ 2, 3, 4, 5, 6, 7, 8, 9, 10])¶
An array object represents a multidimensional, homogeneous array of fixed-size items. An associated data-type object describes the format of each element in the array (its byte-order, how many bytes it occupies in memory, whether it is an integer, a floating point number, or something else, etc.)
Arrays should be constructed using array, zeros or empty (refer to the See Also section below). The parameters given here refer to a low-level method (ndarray(…)) for instantiating an array.
For more information, refer to the numpy module and examine the methods and attributes of an array.
- Parameters:
- (for the __new__ method; see Notes below)
- shape
tuple
of
ints
Shape of created array.
- dtypedata-type,
optional
Any object that can be interpreted as a numpy data type.
- buffer
object
exposing
buffer
interface
,optional
Used to fill the array with data.
- offset
int
,optional
Offset of array data in buffer.
- strides
tuple
of
ints
,optional
Strides of data in memory.
- order{‘C’, ‘F’},
optional
Row-major (C-style) or column-major (Fortran-style) order.
See also
array
Construct an array.
zeros
Create an array, each element of which is zero.
empty
Create an array, but leave its allocated memory unchanged (i.e., it contains “garbage”).
dtype
Create a data-type.
numpy.typing.NDArray
A generic version of ndarray.
Notes
There are two modes of creating an array using
__new__
:If buffer is None, then only shape, dtype, and order are used.
If buffer is an object exposing the buffer interface, then all keywords are interpreted.
No
__init__
method is needed because the array is fully initialized after the__new__
method.Examples
These examples illustrate the low-level ndarray constructor. Refer to the See Also section above for easier ways of constructing an ndarray.
First mode, buffer is None:
>>> np.ndarray(shape=(2,2), dtype=float, order='F') array([[0.0e+000, 0.0e+000], # random [ nan, 2.5e-323]])
Second mode:
>>> np.ndarray((2,), buffer=np.array([1,2,3]), ... offset=np.int_().itemsize, ... dtype=int) # offset = 1*itemsize, i.e. skip first element array([2, 3])
- Attributes:
- T
ndarray
Transpose of the array.
- data
buffer
The array’s elements, in memory.
- dtype
dtype
object
Describes the format of the elements in the array.
- flags
dict
Dictionary containing information related to memory use, e.g., ‘C_CONTIGUOUS’, ‘OWNDATA’, ‘WRITEABLE’, etc.
- flat
numpy.flatiter
object
Flattened version of the array as an iterator. The iterator allows assignments, e.g.,
x.flat = 3
(See ndarray.flat for assignment examples; TODO).- imag
ndarray
Imaginary part of the array.
- real
ndarray
Real part of the array.
- size
int
Number of elements in the array.
- itemsize
int
The memory use of each array element in bytes.
- nbytes
int
The total number of bytes required to store the array data, i.e.,
itemsize * size
.- ndim
int
The array’s number of dimensions.
- shape
tuple
of
ints
Shape of the array.
- strides
tuple
of
ints
The step-size required to move from one element to the next in memory. For example, a contiguous
(3, 4)
array of typeint16
in C-order has strides(8, 2)
. This implies that to move from element to element in memory requires jumps of 2 bytes. To move from row-to-row, one needs to jump 8 bytes at a time (2 * 4
).- ctypes
ctypes
object
Class containing properties of the array needed for interaction with ctypes.
- base
ndarray
If the array is a view into another array, that array is its base (unless that array is also a view). The base array is where the array data is actually stored.
- T


Setup HTML
Introduction
We are using gulp which allows having complete automation for build flow. In case if you don't know Gulp then it's easy to use it. Gulp is a toolkit for automating painful or time-consuming tasks in the development workflow, so you can stop messing around while building any project. You can read it more about it here. Please follow below steps to install and setup all prerequisites:
Prerequisites
Please follow below steps to install and setup all prerequisites:
-
Yarn
Make sure to have the Yarn installed & running in your computer. If you already have installed Yarn on your computer, you can skip this step. We suggest you to use Yarn instead of NPM.
-
Nodejs
Make sure to have the Node.js installed & running in your computer. If you already have installed Node on your computer, you can skip this step if your existing node version is greater than 10.
-
Gulp
Make sure to have the Gulp installed & running in your computer. If you already have installed gulp on run command
npm install -g gulp
from your terminal. -
Git
Make sure to have the Git installed globally & running on your computer. If you already have installed git on your computer, you can skip this step.
Installation
To setup the admin theme, follow below-mentioned steps:
-
Install Prerequisites
Make sure to have all above prerequisites installed & running on your computer
After you finished with the above steps, you can run the following commands into the terminal / command prompt from the root directory of the project to run the project locally or build for production use:
| Command | Description |
|---|---|
yarn install
|
This would install all the required dependencies in
the node_modules folder.
|
gulp
|
Runs the project locally, starts the development server and watches for any changes in your code, including your HTML, javascript, sass, etc. The development server is accessible at http://localhost:3000. |
gulp build
|
Generates a /dist directory with all
the production files.
|
Multi Language Settings
Lets add french language.
- Create new file fr.json in the fr folder in the
src/assets/lang
folder and copy the en.json file code in this file. -
Now you need to add the language in the
src/assets/js/lang/jquery.multiLanguage.js
file. In the function setLanguage add the "else if" condition as below and make sure to add french.jpg file.else if(lang=='fr') { document.getElementById("header-lang-img").src = "assets/images/flags/french.jpg"; }
- You can simply use in the HTML file to convert the language text just add the attribute "key" to the parent div or any HTML tag. Example:
This is title.

Tips
SCSS: We suggest you to do not change any scss files from the assets/scss/custom folders because to get new updates will might be break your SCSS changes if any you have made. We strongly suggest you to create new custom.scss file and use that instead of overwrite any theme's custom scss files.


--- layout: doc title: Documentation ---
A proof assistant is a computerized helper for developing mathematical proofs. For short, we sometimes call it a prover, although we always have in mind an interactive system rather than a fully automated theorem prover.
A proof script is a sequence of commands which constructs a proof, usually stored in a file.
Some proof assistants provide some level of support for switching between multiple concurrent proofs, but Proof General does not use this. Generally the exact context for such proofs is hard to define to easily split them into multiple files.
In fact, this is an unnecessary restriction imposed by the original design of Proof General. There is nothing to stop future versions of Proof General allowing the queue region to be extended or shrunk, whilst the prover is processing it. Proof General 3.0 already relaxes the original design, by allowing successive assertion commands without complaining.
The suffix may depend of the specific proof assistant you are using e.g, LEGO’s proof script files have to end with ‘.l’.
For example, LEGO generates additional compiled (optimised) proof script files for efficiency.
And please, don’t even think of including those in your LEGO proof script!
This document was generated by Erik Martin-Dorel on September 18, 2016 using texi2html 1.82.


This site provides the data used in the study “Developers' Viewpoints on Avoiding Bug-introducing Changes” .
Section 3.1 and 3.2 - Preliminary Assumptions and Q-Set
This Page (Assumptions) present the entire list of assumptions collected from our study.
Section 3.5 - Participant's responses through Q-Sorting process
This Page (Responses) provides the dataset of our study containing the response using our online web Tool.
Section 3.5 - Q Sorting Process: Invitation Letter
This Page (Letter) provides the invitation letter used to invite developers to our study.
Section 3.5 - Q Sorting Process: Questionnaire
This Page (Questionnaire) present the characterization questionnaire used in our study.
Section 3.6 - Conducting the Viewpoint Analysis: Initial Matrix
This Page (Initial Data Matrix) present a two-dimensional matrix obtained from the 41 participants and assumptions.
Section 3.6 - Conducting the Viewpoint Analysis: Correlation Matrix
This Page (Correlation Matrix) shown a correlation matrix between participants (q-sorts) and assumptions.
Section 3.6 - Conducting the Viewpoint Analysis: Initial Viewpoints and Viewpoints Rotation
This Page (Viewpoint Analysis) shown the entire viewpoint analysis.
Section 4.2 - Results and Discussions: Participant's Comments (RQ2)
This Page (Participant's Comments) shown the comments of all participants of our experiment using the Q-Methodology.
Glossary - Terminologies and Statistical Tests
This Page (Glossary) shown the description about the terminologies and statistical tests used in our study.


--- title: Point & Click author: Ben Pirt layout: app stylesheets: - point-click/main.css description: Click to control Mirobot and see the program it would use manifest: /assets/apps/point-click/point-click.manifest ---
{% javascript point-click/app %}


in the cafeteria
I didn’t mean to be mean
when I told Erika you probably don’t need sunglasses
with a forehead like that
I meant to be precise
I am projecting because I think my eyes stink
I mean sink
more each day
past my skull and inch toward my cerebrum
soon my eyes will be fully submerged
they will rotate 180
and I will see grey matter
dated and labeled
organized into
ascending
safes